library(tidyverse)
#install.packages ("seacarb")
#Gibbs Seawater
library(seacarb)
library(gsw)
library(ggplot2)
hydrostation_bottle <- read_delim("hydrostation_bottle.txt",
delim = "\t", escape_double = FALSE,
col_names = FALSE, trim_ws = TRUE, skip = 31)
hydrostation_bottle_names <- read_csv("hydrostation_bottle.txt",
skip = 30)
#Fix names for the dataset
colnames(hydrostation_bottle) = colnames(hydrostation_bottle_names)
view(hydrostation_bottle)
hydrostation_bottle %>%
filter(`Sig-th` != -999 & Depth < 20) %>%
ggplot()+
geom_point(aes(x = decy, y = `Sig-th`))+
geom_line(aes(x =decy, y = `Sig-th` ))
#Clear Seasonal signal for sigma-theta
hydrostation_bottle %>%
filter(`Sig-th` != -999 & Depth < 20) %>%
ggplot()+
geom_point(aes(x =Temp, y = `Sig-th` ))
#Density and Temperature are strongly correlated, but there appears to be two outliners that we will likely need to address at some point
#We only have density data from 1988-present, but temperature and salinity data from 1950s-present, this mean i can calculate seawater density from 1950s- present, by using TEOS-10.
#Has surface sigma theta decreased over time?
HydroS_Shallow = HydroS_corrected %>%
filter(Depth<30)
?lm
## starting httpd help server ... done
#lm(y is a function(~) of x)
lm(sig_theta_gsw~decy,data = HydroS_Shallow)
##
## Call:
## lm(formula = sig_theta_gsw ~ decy, data = HydroS_Shallow)
##
## Coefficients:
## (Intercept) decy
## 56.28396 -0.01563
#y = mx+b
#Coeficients: intercept = b, decy = m
#Sig_theta_gws = -0.01563*decy + 56.28
#(kg/m^3) = (kg/m^3/x)*x + (kg/m^3)
sig_theta_model = lm(sig_theta_gsw~decy,data = HydroS_Shallow)
summary(sig_theta_model)
##
## Call:
## lm(formula = sig_theta_gsw ~ decy, data = HydroS_Shallow)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.6372 -0.8673 0.1377 0.8460 1.6206
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 56.28396 4.39141 12.817 < 2e-16 ***
## decy -0.01563 0.00219 -7.139 1.31e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9219 on 2001 degrees of freedom
## Multiple R-squared: 0.02483, Adjusted R-squared: 0.02435
## F-statistic: 50.96 on 1 and 2001 DF, p-value: 1.313e-12
library(plotly)
##
## Attaching package: 'plotly'
##
## The following object is masked from 'package:ggplot2':
##
## last_plot
##
## The following object is masked from 'package:stats':
##
## filter
##
## The following object is masked from 'package:graphics':
##
## layout
Sig_decy_plot = HydroS_Shallow %>%
ggplot(aes(x = decy, y = sig_theta_gsw))+
geom_point()+
geom_line()+
geom_smooth(method = "lm")+
theme_classic()
ggplotly(Sig_decy_plot)
## `geom_smooth()` using formula 'y ~ x'
Hypothesis: Temperature have a greater effect on density in the surface layer.
Densityplot=
HydroS_corrected%>%
filter(Depth<150) %>%
ggplot()+
geom_point(aes(x=Depth,y= sig_theta_gsw))+
xlab('Depth (m)')+
ylab('Sig-theta (kg/m^3)')+
scale_y_reverse()+
scale_x_continuous(position ="bottom")
Densityplot
Densityplot=
HydroS_corrected%>%
filter(Depth<150) %>%
ggplot()+
geom_point(aes(x=Depth,y= sig_theta_gsw))+
xlab('Depth (m)')+
ylab('Sig-theta (kg/m^3)')+
scale_y_reverse()+
scale_x_continuous(position ="bottom")
Describe your results, the summary, and answer the question
Compile into a completed lab report using R Markdown
Potential questions: how do temp, sal, and sigma-theta co-vary Is there a relationship between sigma-theta and oxygen? Is there a relationship of any of the parameter with depth? with time? within depth over time? Are there seasonal differences in any of the parameters?